10 papers
TRACER: Token ReAssignment for Concept ERasure in Generative Recommendation
Ziheng Chen, Jiali Cheng, Zezhong Fan +4
Generative recommendation formulates next-item prediction as autoregressive generation over semantic ID (SID) sequences derived from users' historical interactions, making modern r…
YOCO++: Enhancing YOCO with KV Residual Connections for Efficient LLM Inference
You Wu, Ziheng Chen, Yizhen Zhang +6
Cross-layer key-value (KV) compression has been found to be effective in efficient inference of large language models (LLMs). Although they reduce the memory consumption of the KV…
CRAB: Codebook Rebalancing for Bias Mitigation in Generative Recommendation
Zezhong Fan, Ziheng Chen, Luyi Ma +5
Generative recommendation (GeneRec) has introduced a new paradigm that represents items as discrete semantic tokens and predicts items in a generative manner. Despite its strong pe…
CURE:Circuit-Aware Unlearning for LLM-based Recommendation
Ziheng Chen, Jiali Cheng, Zezhong Fan +4
Recent advances in large language models (LLMs) have opened new opportunities for recommender systems by enabling rich semantic understanding and reasoning about user interests and…
MIBench: Evaluating LMMs on Multimodal Interaction
Yu Miao, Zequn Yang, Yake Wei +5
In different multimodal scenarios, it needs to integrate and utilize information across modalities in a specific way based on the demands of the task. Different integration ways be…
HEEGNet: Hyperbolic Embeddings for EEG
Shanglin Li, Shiwen Chu, Okan Koç +4
Electroencephalography (EEG)-based brain-computer interfaces facilitate direct communication with a computer, enabling promising applications in human-computer interactions. Howeve…